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Vector store support for Cassandra #6426

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hemidactylus
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This addresses #6291 adding support for using Cassandra (and compatible databases, such as DataStax Astra DB) as a Vector Store.

A new class Cassandra is introduced, which complies with the contract and interface for a vector store, along with the corresponding integration test, a sample notebook and modified dependency toml.

Dependencies: the implementation relies on the library cassio, which simplifies interacting with Cassandra for ML- and LLM-oriented workloads. CassIO, in turn, uses the cassandra-driver low-lever drivers to communicate with the database. The former is added as optional dependency (+ in extended_testing), the latter was already in the project.

Integration testing relies on a locally-running instance of Cassandra. Here a detailed description can be found on how to compile and run it (at the time of writing the feature has not made it yet to a release).

During development of the integration tests, I added a new "fake embedding" class for what I consider a more controlled way of testing the MMR search method. Likewise, I had to amend what looked like a glitch in the behaviour of ConsistentFakeEmbeddings whereby an embed_query call would have bypassed storage of the requested text in the class cache for use in later repeated invocations.

@dev2049 might be the right person to tag here for a review. Thank you!

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looks great - thanks!

@hwchase17 hwchase17 added the 03 enhancement Enhancement of existing functionality label Jun 20, 2023
@rlancemartin rlancemartin force-pushed the SL-cassandra-vector-store branch 4 times, most recently from 155acaa to 95ce962 Compare June 20, 2023 17:34
@rlancemartin rlancemartin force-pushed the SL-cassandra-vector-store branch from 95ce962 to b0d9b7e Compare June 20, 2023 17:38
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Great work! I resolved the lint errors.

@rlancemartin rlancemartin merged commit 22af93d into langchain-ai:master Jun 20, 2023
bdonkey added a commit to bdonkey/langchain that referenced this pull request Jun 20, 2023
* master: (158 commits)
  Fix link (langchain-ai#6501)
  docs/fix links (langchain-ai#6498)
  Update notebook for MD header splitter and create new cookbook (langchain-ai#6399)
  Vector store support for Cassandra (langchain-ai#6426)
  improve documentation on base chain (langchain-ai#6468)
  fix: change ddg to DDGS (langchain-ai#6480)
  release 207 (langchain-ai#6488)
  Add Alibaba Cloud OpenSearch as a new vector store (langchain-ai#6154)
  fix openai qa chain (langchain-ai#6487)
  add FunctionMessage support to `_convert_dict_to_message()` in OpenAI chat model (langchain-ai#6382)
  bump version to 206 (langchain-ai#6465)
  fix neo4j schema query (langchain-ai#6381)
  Update serpapi.py Support baidu list type answer_box (langchain-ai#6386)
  fix: llm caching for replicate (langchain-ai#6396)
  feat: use latest duckduckgo_search API to call (langchain-ai#6409)
  Harrison/unstructured page number (langchain-ai#6464)
  Improve error message (langchain-ai#6275)
  Fix the issue where ANTHROPIC_API_URL set in environment is not takin… (langchain-ai#6400)
  Fix broken links in autonomous agents docs (langchain-ai#6398)
  Update SinglStoreDB vectorstore (langchain-ai#6423)
  ...
@hemidactylus hemidactylus deleted the SL-cassandra-vector-store branch June 22, 2023 08:41
This was referenced Jun 25, 2023
rlancemartin pushed a commit that referenced this pull request Jun 29, 2023
### Overview

This PR aims at building on #4378, expanding the capabilities and
building on top of the `cassIO` library to interface with the database
(as opposed to using the core drivers directly).

Usage of `cassIO` (a library abstracting Cassandra access for
ML/GenAI-specific purposes) is already established since #6426 was
merged, so no new dependencies are introduced.

In the same spirit, we try to uniform the interface for using Cassandra
instances throughout LangChain: all our appreciation of the work by
@jj701 notwithstanding, who paved the way for this incremental work
(thank you!), we identified a few reasons for changing the way a
`CassandraChatMessageHistory` is instantiated. Advocating a syntax
change is something we don't take lighthearted way, so we add some
explanations about this below.

Additionally, this PR expands on integration testing, enables use of
Cassandra's native Time-to-Live (TTL) features and improves the phrasing
around the notebook example and the short "integrations" documentation
paragraph.

We would kindly request @hwchase to review (since this is an elaboration
and proposed improvement of #4378 who had the same reviewer).

### About the __init__ breaking changes

There are
[many](https://docs.datastax.com/en/developer/python-driver/3.28/api/cassandra/cluster/)
options when creating the `Cluster` object, and new ones might be added
at any time. Choosing some of them and exposing them as `__init__`
parameters `CassandraChatMessageHistory` will prove to be insufficient
for at least some users.

On the other hand, working through `kwargs` or adding a long, long list
of arguments to `__init__` is not a desirable option either. For this
reason, (as done in #6426), we propose that whoever instantiates the
Chat Message History class provide a Cassandra `Session` object, ready
to use. This also enables easier injection of mocks and usage of
Cassandra-compatible connections (such as those to the cloud database
DataStax Astra DB, obtained with a different set of init parameters than
`contact_points` and `port`).

We feel that a breaking change might still be acceptable since LangChain
is at `0.*`. However, while maintaining that the approach we propose
will be more flexible in the future, room could be made for a
"compatibility layer" that respects the current init method. Honestly,
we would to that only if there are strong reasons for it, as that would
entail an additional maintenance burden.

### Other changes

We propose to remove the keyspace creation from the class code for two
reasons: first, production Cassandra instances often employ RBAC so that
the database user reading/writing from tables does not necessarily (and
generally shouldn't) have permission to create keyspaces, and second
that programmatic keyspace creation is not a best practice (it should be
done more or less manually, with extra care about schema mismatched
among nodes, etc). Removing this (usually unnecessary) operation from
the `__init__` path would also improve initialization performance
(shorter time).

We suggest, likewise, to remove the `__del__` method (which would close
the database connection), for the following reason: it is the
recommended best practice to create a single Cassandra `Session` object
throughout an application (it is a resource-heavy object capable to
handle concurrency internally), so in case Cassandra is used in other
ways by the app there is the risk of truncating the connection for all
usages when the history instance is destroyed. Moreover, the `Session`
object, in typical applications, is best left to garbage-collect itself
automatically.

As mentioned above, we defer the actual database I/O to the `cassIO`
library, which is designed to encode practices optimized for LLM
applications (among other) without the need to expose LangChain
developers to the internals of CQL (Cassandra Query Language). CassIO is
already employed by the LangChain's Vector Store support for Cassandra.

We added a few more connection options in the companion notebook example
(most notably, Astra DB) to encourage usage by anyone who cannot run
their own Cassandra cluster.

We surface the `ttl_seconds` option for automatic handling of an
expiration time to chat history messages, a likely useful feature given
that very old messages generally may lose their importance.

We elaborated a bit more on the integration testing (Time-to-live,
separation of "session ids", ...).

### Remarks from linter & co.

We reinstated `cassio` as a dependency both in the "optional" group and
in the "integration testing" group of `pyproject.toml`. This might not
be the right thing do to, in which case the author of this PR offer his
apologies (lack of confidence with Poetry - happy to be pointed in the
right direction, though!).

During linter tests, we were hit by some errors which appear unrelated
to the code in the PR. We left them here and report on them here for
awareness:

```
langchain/vectorstores/mongodb_atlas.py:137: error: Argument 1 to "insert_many" of "Collection" has incompatible type "List[Dict[str, Sequence[object]]]"; expected "Iterable[Union[MongoDBDocumentType, RawBSONDocument]]"  [arg-type]
langchain/vectorstores/mongodb_atlas.py:186: error: Argument 1 to "aggregate" of "Collection" has incompatible type "List[object]"; expected "Sequence[Mapping[str, Any]]"  [arg-type]

langchain/vectorstores/qdrant.py:16: error: Name "grpc" is not defined  [name-defined]
langchain/vectorstores/qdrant.py:19: error: Name "grpc" is not defined  [name-defined]
langchain/vectorstores/qdrant.py:20: error: Name "grpc" is not defined  [name-defined]
langchain/vectorstores/qdrant.py:22: error: Name "grpc" is not defined  [name-defined]
langchain/vectorstores/qdrant.py:23: error: Name "grpc" is not defined  [name-defined]
```

In the same spirit, we observe that to even get `import langchain` run,
it seems that a `pip install bs4` is missing from the minimal package
installation path.

Thank you!
vowelparrot pushed a commit that referenced this pull request Jul 4, 2023
### Overview

This PR aims at building on #4378, expanding the capabilities and
building on top of the `cassIO` library to interface with the database
(as opposed to using the core drivers directly).

Usage of `cassIO` (a library abstracting Cassandra access for
ML/GenAI-specific purposes) is already established since #6426 was
merged, so no new dependencies are introduced.

In the same spirit, we try to uniform the interface for using Cassandra
instances throughout LangChain: all our appreciation of the work by
@jj701 notwithstanding, who paved the way for this incremental work
(thank you!), we identified a few reasons for changing the way a
`CassandraChatMessageHistory` is instantiated. Advocating a syntax
change is something we don't take lighthearted way, so we add some
explanations about this below.

Additionally, this PR expands on integration testing, enables use of
Cassandra's native Time-to-Live (TTL) features and improves the phrasing
around the notebook example and the short "integrations" documentation
paragraph.

We would kindly request @hwchase to review (since this is an elaboration
and proposed improvement of #4378 who had the same reviewer).

### About the __init__ breaking changes

There are
[many](https://docs.datastax.com/en/developer/python-driver/3.28/api/cassandra/cluster/)
options when creating the `Cluster` object, and new ones might be added
at any time. Choosing some of them and exposing them as `__init__`
parameters `CassandraChatMessageHistory` will prove to be insufficient
for at least some users.

On the other hand, working through `kwargs` or adding a long, long list
of arguments to `__init__` is not a desirable option either. For this
reason, (as done in #6426), we propose that whoever instantiates the
Chat Message History class provide a Cassandra `Session` object, ready
to use. This also enables easier injection of mocks and usage of
Cassandra-compatible connections (such as those to the cloud database
DataStax Astra DB, obtained with a different set of init parameters than
`contact_points` and `port`).

We feel that a breaking change might still be acceptable since LangChain
is at `0.*`. However, while maintaining that the approach we propose
will be more flexible in the future, room could be made for a
"compatibility layer" that respects the current init method. Honestly,
we would to that only if there are strong reasons for it, as that would
entail an additional maintenance burden.

### Other changes

We propose to remove the keyspace creation from the class code for two
reasons: first, production Cassandra instances often employ RBAC so that
the database user reading/writing from tables does not necessarily (and
generally shouldn't) have permission to create keyspaces, and second
that programmatic keyspace creation is not a best practice (it should be
done more or less manually, with extra care about schema mismatched
among nodes, etc). Removing this (usually unnecessary) operation from
the `__init__` path would also improve initialization performance
(shorter time).

We suggest, likewise, to remove the `__del__` method (which would close
the database connection), for the following reason: it is the
recommended best practice to create a single Cassandra `Session` object
throughout an application (it is a resource-heavy object capable to
handle concurrency internally), so in case Cassandra is used in other
ways by the app there is the risk of truncating the connection for all
usages when the history instance is destroyed. Moreover, the `Session`
object, in typical applications, is best left to garbage-collect itself
automatically.

As mentioned above, we defer the actual database I/O to the `cassIO`
library, which is designed to encode practices optimized for LLM
applications (among other) without the need to expose LangChain
developers to the internals of CQL (Cassandra Query Language). CassIO is
already employed by the LangChain's Vector Store support for Cassandra.

We added a few more connection options in the companion notebook example
(most notably, Astra DB) to encourage usage by anyone who cannot run
their own Cassandra cluster.

We surface the `ttl_seconds` option for automatic handling of an
expiration time to chat history messages, a likely useful feature given
that very old messages generally may lose their importance.

We elaborated a bit more on the integration testing (Time-to-live,
separation of "session ids", ...).

### Remarks from linter & co.

We reinstated `cassio` as a dependency both in the "optional" group and
in the "integration testing" group of `pyproject.toml`. This might not
be the right thing do to, in which case the author of this PR offer his
apologies (lack of confidence with Poetry - happy to be pointed in the
right direction, though!).

During linter tests, we were hit by some errors which appear unrelated
to the code in the PR. We left them here and report on them here for
awareness:

```
langchain/vectorstores/mongodb_atlas.py:137: error: Argument 1 to "insert_many" of "Collection" has incompatible type "List[Dict[str, Sequence[object]]]"; expected "Iterable[Union[MongoDBDocumentType, RawBSONDocument]]"  [arg-type]
langchain/vectorstores/mongodb_atlas.py:186: error: Argument 1 to "aggregate" of "Collection" has incompatible type "List[object]"; expected "Sequence[Mapping[str, Any]]"  [arg-type]

langchain/vectorstores/qdrant.py:16: error: Name "grpc" is not defined  [name-defined]
langchain/vectorstores/qdrant.py:19: error: Name "grpc" is not defined  [name-defined]
langchain/vectorstores/qdrant.py:20: error: Name "grpc" is not defined  [name-defined]
langchain/vectorstores/qdrant.py:22: error: Name "grpc" is not defined  [name-defined]
langchain/vectorstores/qdrant.py:23: error: Name "grpc" is not defined  [name-defined]
```

In the same spirit, we observe that to even get `import langchain` run,
it seems that a `pip install bs4` is missing from the minimal package
installation path.

Thank you!
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